Exploring the Dimensions of Self-Efficacy in Virtual World Learning (Do not exceed 6000 words, excluding abstract and references)
Questions for Chuck and Patsy: The survey number is high. How should we graphically show the data?
Steven: Will talk more about the tutorials the students used to prepare them for the assignments. He will expand on the part where I say it's good to have objects that give immediate feedback. This feedback allows students to interact with the equation and retry.
Random Notes to Incorporate:
Functionality = AE
Interacting with objects = AS
We are also looking at content.
SL is unique from other applications in that you have a sense of place and body.
It is also more technically complex than other applications.
Self-efficacy is a concern - getting around it, but also learning the content.
Self-efficacy is dimensional with regards to learning, especially with technology. What are the dimensions, how has this been studied in the past? Johnson went with AS and AE; a general self-efficacy was not enough to fully appreciate learners' abilities/needs. We are going to identify the dimensions of self-efficacy in SL, rather than basic computer software. SL has the extras like avatars, communicating with others, etc. We are going to look at it from the perspective of an academic class as well.
We need to define AE and AS in our context.
How was self-efficacy been studied with regards to virtual worlds? Merchant and Chow both looked at it in different ways. Merchant was more general self-efficacy in the content (chemistry), and Chow looked at usability, ease of use, etc. While these are both promising and drove our research, we want to expand on those findings by looking at the dimensions of self-efficacy that comes with learning in this environment.
Chow: Ease of use was an issue.
Steven gave students questions to measure self-efficacy, and we wanted to see if the questions fell into these categories (AE and AS). Content emerged as important. Those believing in their ability to use the LOs were more likely to believe in their ability to understand the equation; likewise, those understanding the equation were more likely to believe in their ability to use the LOs. We want to understand these factors more in our next research; determine some causation.
Next Steps: In this look, we are simply measuring whether they have self-efficacy or not. We are not looking into how they got self-efficacy in the first place. Next time we will look at the influences of certain approaches/guides to help students gain self-efficacy. For instance, Steven created a tutorial -- when students used this, their questions about how to use SL went down dramatically. If they have more AS, then their AE and content are likely to be positively influenced. What should be in a good orientation?
At the end - we know more about the dimensions of self-efficacy. Measuring self-efficacy in one way is not enough. There is AE, AS, and the content itself.
Abstract
Virtual worlds offer learners an enhanced sense of user presence and community, opportunities for experiential experiences, and user-centered design of the environment. However, virtual worlds are more technically complex than technologies typically used in educational settings and require students to interact in novel ways for learning to occur. Self-efficacy, the beliefs a person has about her capabilities to successfully perform a particular behavior or task, could be a critical element toward understanding student learning with the virtual world. The purpose of our study is to explore the dimensionality of students’ self-efficacy concerning learning academic content in the virtual world of Second Life. Students in an accounting class participated in several virtual world activities to learn content. Through analysis of a survey, three dimensions of self-efficacy were identified: functionality in virtual worlds; content mediated by virtual world; and content. The findings of this study offer an insight into the critical instructional design issues that must be addressed in order for effective learning to be realized in virtual worlds.
Introduction
[Aimee will expand] Technologies that place the user at the center of learning are rapidly being incorporated in higher education. The features of social media complement the constructivist philosophy of teaching and learning, allowing learners to create, co-create and share knowledge with a global audience beyond classroom walls. In addition, social media is tremendously popular in learners’ social lives.
One such innovative technology being integrated in educational environments is the three-dimensional virtual world. Most virtual worlds, such as Second Life, physically resemble three-dimensional Earth in varying degrees, with typical depictions of land, sky, and water. Both designers and users can shape the design, content and objectives of the world, which is perpetual and persistent (Book, 2004). [Expand on this more, give examples maybe]
SL is different. Unlike most other social media applications, virtual worlds stimulate a feeling of actually being located in the virtual space (Mennecke, Hassall, & Triplett, 2008). Users are represented by avatars, simulated bodies in which users sensually perceive the virtual world. Compared to other online technologies, there is a heightened sense of user presence due to the embodied nature of avatars. In contrast to a video game in which an avatar represents a character, in a social virtual world, the avatar is intended to represent the user. Loke (2009) explains, “SL is not simply a game where players, detached from their avatars, control the avatars for pure entertainment…It’s not simply a uniform, but self-representation” (p. 148). With roots in social media and games, virtual worlds are predicated on social interaction. Virtual worlds are multi-user, meaning that multiple users share the same space and interact in ‘real time’. Regarding interaction, avatars occupy the same space and communication is mediated by the body; written text, spoken voice and body language. Because of this shared experience, common ground can be created and sustained, eliciting a feeling of co-presence, that the user is really with another person (Jarmon, 2009). As the user directs the avatar through the 3D space, the computer generates graphics in real time to give the user visual and auditory feedback on their position in the environment (Jones, Morales, & Knezek, 2005). Just as humans in the ‘real world’, avatars dynamically interact with objects and each other.
They are becoming more integrated into educational environments. Past studies have found that the virtual world learning environment engages students (Hornik & Thornburg, 2010; Meggs et al., 2011; Mennecke et al., 2008), and can lead to improved performance (Hornik & Thornburg, 2010). The unique affordances of virtual worlds help to explain these findings. First, they have been found to support a sense of community among learners. Regarding community, McKerlich, Rils, Anderson, and Eastman (2011) found that participants did in fact experience a community of inquiry in a virtual world learning environment. Specifically three types of user presence were identified: social (avatar expression, group activities), cognitive (discussions, building) and teaching (text, IM, notecards). It provided a forum for wide collaboration with the potential to link students to the professional world (Meggs). The affordances of the space also allow novel ways to create content and sense of place (Hornik & Thornburg, 2010), which supports multiple learning styles (Meggs et al., 2011). Due to the open-ended nature and customizability of the environment, it can be used for all kinds of disciplines and objectives.
It has the ability to be free from worldly time and space hindrances as well. Meggs, Greer, and Collins (2011) found that the use of SL facilitated instructional practices that allowed for experiential activities which would not have been otherwise available. By learning in virtual worlds, students can make connections to subjects previously seen as abstract. Merchant talks about them learning chemistry concepts by rotating chemistry models through their avatars. Students can receive instant feedback through interacting with objects and from others in the environment. For example, Meggs et al. (2011) found that virtual note cards aided students in making corrections to their thinking (Steven kind of did this).
But there are hindrances; SL is tough. The learning curve required for SL has been documented by many (Collins, personal communication; Mayrath, Traphagan, Heikes, & Trivedi, 2009; Sanchez, 2007). One consistent theme in the literature is that learners often report technical difficulties when participating in SL (Mayrath et al., 2009; Mennecke et al., 2008; Sanchez, 2007). Student technical skill and experience with virtual worlds significantly impact a student’s learning experience. Students often report difficulties with the interface (Mennecke et al., 2008), with interaction with objects like media or notecards (deNoyelles, 2012), with navigation (deNoyelles, 2012), and with communication with others (Mennecke et al., 2008). Chow et al. (2012) found that ease of use was a factor, and they identified a need to boost self-confidence when using the system.This makes it difficult or impossible to build and shape content within the environment (deNoyelles, 2012). Merchant et al. (2012) found that usability influenced the learning of content. All of these factors impact learning. Supporting students to learn content is difficult here.
(So they need to feel control of their avatars and with the objects they need to interact with in order to get a learning benefit from it.)
(SL is different and tough; Self-efficacy is important) In order to navigate through the environment and customize content (ease the use), the student must take control and make decisions, leading to immersion in the learning process and positively affecting motivation (Dieterle & Clarke, 2007; Malone & Lepper, 1987). However, in order to take control and make decisions in the virtual world, one must perceive an adequate level of self-efficacy, defined as beliefs a person has about her capabilities to successfully perform a particular behavior or task (Merchant, Goetz, Keeney-Kennicutt, Kwok, Cifuentes, & Davis, 2012). Bandura (1997) described self-efficacy as "beliefs in one's capabilities to organize and execute the courses of action required to produce given attainments" (p. 3). It is thought that self-efficacy influences the behavior someone is willing to engage it, the extent to which the behavior is successful, the persistence one maintains in the face of obstacles, and coping mechanisms used when encountering adverse situations (Johnson, 2005). These characteristics make self-efficacy a key characteristics for leveraging the promise of virtual worlds. Self-efficacy is an area that is not fully understood in the virtual world environment, which is concerning given that virtual worlds are technically more complex than other kinds of social media being used in classrooms. Self-efficacy could be a critical element toward understanding student learning within the virtual world. In particular, a factor associated with self-efficacy is the ability to interact and control the learning environment (Bandura, 1993).
(Self-efficacy has dimensions) How have others studied self-efficacy? Similar to the current interest in self-efficacy with respect to virtual worlds, the information systems community examined this construct in the late 1990's while investigating causes related to end-user's adoption and use of computer technology. This research focused on the need to move beyond a general self-efficacy measure to examine self-efficacy as it related specifically to the task in question - computer self-efficacy (Compeau and Higgins, 1995; Marakas, Mun, and Johnson,1998; Johnson, 2005). In this research computer self-efficacy was referred to a users "judgement of one's capability to use a computer" (Compeau and Higgins, 1995, p. 192). Marakas et al. (1998) proposed that like general self-efficacy, 'general' computer self-efficacy was too broad a construct and argued for the use of task specific measures. Johnson (2005) defined these task specific constructs as Application-environment computer self-efficacy (AE) and Application-specific computer self-effiacy (AS). AE is an individual's belief in their ability to complete tasks common to an application environment (e.g. navigate in SL). AS is an individual's belief in their ability to complete a task specific to an application (e.g. interacting with objects within learning objects within SL). It is important when studying the impact of self-efficacy within virtual worlds to take use these more nuanced constructs to be able to examine the various aspects in a learner's belief that can influent their use and eventual benefit that may derive from learning with virtual worlds. That is, a learner must first be able to use the SL platform in general (AE) before they can be expected to be comfortable to work with learning objects designed for a specific learning content area (AS) (in our study, we test this out). As argued by Marakas et al. (1998, p. 129), "by focusing on the appellation independent of the task being performed with it, we can assess an individual's perception of ability to use the tool without constraining or bounding that assessment with a task situation requiring cross-domain knowledge".
(We need to look at the dimensions of self-efficacy in SL) Research about self-efficacy and virtual worlds has begun. Merchant et al. (2012) examined general self-efficacy (self-efficacy for learning chemistry) in SL and found a relationship between self-efficacy and student performance. Being able to control/interact with the environment may influence self-efficacy about learning the content (Merchant). They also found a relationship between the usability of SL and self-efficacy (content), as well as an indirect relationship between the features of SL and self-efficacy (content). They found that self-efficacy has a significant impact on learning content. However, the question of whether usability affects self-efficacy or if self-efficacy affects usability in understanding its impact on learners with regard to virtual worlds can be underscored by Chow et al. (2012) who examined the relationship between computer self-efficacy and learners perceived ease-of use and usefulness of SL (opposite to that of Merchant et al, (2012). A potential limitation with these two studies is that each only examined the concept of general self-efficacy. It is our contention that while the relationship between perceived usability and features is important, it is as important for students to feel they have the ability to use such environments in general and to use immersive learning models more specifically (completing tasks within?).
The purpose of our study is to better understand the dimensionality of the space according to students relating to the academic content in virtual worlds, and to examine the relationships of the various dimensions of virtual world self-efficacy. (Steven asked questions related to general self-efficacy, SL self-efficacy, and 3 dimensions came out).
This paper will therefore examine the relationships between AE-SL (get around SL like navigation) and AS-SL (interacting with objects in SL) and also a third self-efficacy, "content-matter" self-efficacy. It is our belief that perceptions of one's belief in having learned a skill within a visual world environment, they must first believe in their ability to use the environment in general, followed by the belief in their ability to utilize tools within the virtual world. The findings of this study offer an insight into the critical instructional design issues that must be addressed before effective learning can occur in virtual worlds.
Methodology
This research took place in a Financial Accounting course taught in the Spring 2011 semester at a very large university in the southeast United States. The course had a total enrollment of 772 students. The course is a required class and is taught as a video-streaming course which means that students have the option to attend class or watch the classroom presentation via streaming video. The virtual world of Second Life was utilized as a supplement to the class and geared heavily towards the foundational material in the beginning of the course. A foundational learning concept in financial accounting is the accounting equation which states as: Assets = Liabilities + Stockholder's Equity. At first blush it looks like a simple algebraic equation, which it is. But within the realm of financial accounting, adjustments to the variables in the equation (Assets, Liabilities and Stockholder's Equity) are described using the terms 'debit' and 'credit'. In short, any increase to an Asset account requires a debit and any increase in a Liability or Equity account requires a credit. while the reverse is true when decreasing the accounts. It gets more complicated when considering the accounts that compose the equity variable. Without understanding these basic concepts, students are destined for early withdrawal, failure or a semester of considerable time and effort to earn a passing grade.
To help students understand the accounting equation (Assets = Liabilities + Stockholders Equity), a model of it was built in Second Life. This model allowed students to visualize how a debit or credit would increase or decrease the account type and impact the accounting equation, going beyond an abstract algebraic expression to something tangible that can be seen, touched and interacted with (Include Figure here). Two types of these learning models were developed. One type allowed the students to interact with the various parts of the model (Assets, Liabilities, Equity). The students had to "talk" (via text chat) to the models and provide the key words "debit" and/or "credit" followed by a value, after which they would visually see the effect of the command on the 3-D asset increasing or decreasing within the virtual world. They would also receive text-based feedback from the model, such as "Assets 'debited' standby for an Increase". Students used this model to complete various assignments. The first assignment simply had students learn the chat commands to interact with the model, while the next two assignments had students interact with the model with sets of various accounting transactions pertinent to the section of the course that they were learning. The second type of 3-D accounting equation model was in the form of a tutorial. These models were designed to help a student learn basic accounting equations. They could interact with these tutorial models and, for example, learn how to record a collection of cash on account. Additionally, a construct commonly used in teaching financial accounting, the t-account, was also modeled. A t-account is a representation of an account and is used to distinguish the effects of a debit or credit on a specific account balance. Within Second Life, students (through avatars) were able to walk onto a T-account and turn into a debit or credit (interacting with the equation through their simulated bodies). They were then given various accounts and had to determine what was needed to either increase or decrease the account balance (debit or credit) and walk to the proper side (debit or credit) of the t-account. Students would receive feedback from the model as they made their choices.
The majority of these assignments took place during the initial part of the course (all of the 3-D accounting equation assignments) while the t-account assignment was completed during the latter part of the course. Student assignments were captured and sent to a database for grading, and all assignment work was completed within the SL environment.
Data Sources and Collection
After finishing the various Second Life assignments, students were asked to complete surveys related to their experiences. While the survey instrument collected various measures, this paper focuses only on the self-efficacy measures. The measures were constructed based on the methodology described in Marakas, Yi and Johnson (1998). The research data is the result of surveys (n=1377) that were presented to the students at the beginning of the semester and included questions related to self-efficacy. Specifically, the questions related to students perceptions pertaining to their ability to use the Second Life environment (navigation, communication, etc.), their ability to use the 3-D learning objects within Second Life, and their ability to understand the basic accounting concepts. Students received extra credit for completing the surveys.
Data Analysis (Aimee will talk to Chuck more about this)
To assess the dimensionality of student ratings of self-efficacy, the authors used Guttman's image factor analysis (Guttman, 1953). The variables are considered in two parts: that which can be predicted from the rest of the variables in the set (the image) and that which is not predictable from those variables (the anti-image). While the images are similar to common factors, the anti-images are similar to unique factors (Desjardins, 2010). Unlike common factor analysis, this is a multiple correlation approach (Desjardins, 2010). For all of the data, a pattern matrix and correlation matrix were generated.
Results
Three dimensions of self-efficacy were extracted from the data using a pattern matrix. These are: (1) functionality in virtual worlds (application-environment computer self-efficacy); (2) content mediated by SL (application-specific computer self-efficacy); and (3) content. Each category will be explored below, with reference to the statistically strongest survey items for each.
Dimension 1: Functionality in Virtual World (should we rename this AE?)
In line with previous literature, being able to technically function in the virtual world (usability?) emerged as a unique dimension of self-efficacy. Table 1 lists the statements and their corresponding strength.
Statement
Strength
I believe I have the ability to walk around the classroom.
.911
I believe I have the ability to effective navigate the classroom.
.872
I believe I have the ability to fly around the classroom.
.834
I believe I have the ability to move around the classroom.
.820
I believe I have the ability to communicate effectively with others in SL.
.715
I believe I have the ability to interact with objects in SL.
.644
I believe I have the ability to use text-based chat in SL.
.621
I believe I have the ability to have my avatar gesture.
.604
Table 1. Functionality in virtual worlds.
Based on these results, feeling able to control the avatar as it/he/she moves, walks, and flies through the space is critical. Communication with others, such as chatting in text and avatar gestures, is also a factor. Feeling able to interact with objects in the world also emerges. These are all crucial skills that are necessary for student learning in SL to take place. On an interesting note, these results can be expanded to the ‘real world’ as well. To learn effectively, students must feel able to control their bodies in space, communicate with others, and interact with the world. These are the basic elements; simply to function in the virtual world (learning is not addressed here yet).
*In the intro, positives include community and user presence (communication), transcend the real, and interaction with content (interact with objects, world).
Dimension 2: Content Mediated by Virtual World (should we rename this AS?)
Another dimension of self-efficacy is the students’ belief in their ability to interact with the academic content (in this case, accounting learning objects) mediated by the virtual world. Table 2 displays the survey items in this dimension.
Statement
Strength
I believe I have the ability to manipulate the accounting equation in SL.
.941
I believe I have the ability to use the accounting equation in SL.
.840
I believe I have the ability to manipulate the t-accounts in SL.
.837
I believe I have the ability to use credits to interact with the accounting equation.
.811
I believe I have the ability to use debits to interact with the accounting equation.
.807
Table 2. Content mediated by SL.
Feeling able to “manipulate” and “use” learning objects embedded in the virtual world emerges as its own dimension of self-efficacy. Being able to use objects (like credits and debits) in order to “interact” with the equation also comes out. This is an interesting notion; in this case, users also interact with the accounting equation by standing in a certain spot, which is a novel way to learn accounting.
Certainly, this dimension is related to the first dimension, ‘functionality in virtual worlds.’ One must move their avatar through the virtual world space in order to get to the accounting objects. Another factor to consider is their self-efficacy concerning the academic content in general.
Dimension 3: Academic Content
Finally, self-efficacy regarding the accounting content emerged as the final dimension (Table 3). Students’ beliefs in the ability to properly identify the debit and credit part of a transaction were important. Note that these statements are completely separate from the activities experienced in SL.
Statement
Strength
I believe I have the ability to properly identify the debit part(s) of a transaction.
.713
I believe I have the ability to properly identify the credit part(s) of a transaction.
.690
Table 3. Content.
A correlation matrix of the data reveals that these three dimensions of self-efficacy are highly correlated (Table 4). For instance, if students believe in their ability to navigate in the SL classroom, they are also likely to believe in their ability to manipulate accounting content in SL (.730), and more likely to believe in their knowledge of the accounting content (.677). Following this line of thinking, if one does not believe in their ability to use the accounting equation in SL, they are less likely to function well in SL, and less likely to have high self-efficacy regarding their knowledge of the accounting content. The implications of this are discussed in the next section.
Factor
1 (Functionality in SL)
2 (Content mediated by SL)
3 (Content)
1
1.000
.730
.677
2
.730
1.000
.707
3
.677
.707
1.000
Table 4. Factor Correlation Matrix
Discussion
The implications of this study are powerful, as it supports our assertion that a single construct of self-efficacy regarding virtual worlds is not sufficient to gauge whether students will be successful learners in these environments. Our results identify three dimensions of self-efficacy that are relevant for learners and meaningful learning. It is clear that students must feel able to technically navigate and interact with the virtual world (other studies support this like Chow and Merchant) (AE). If they cannot, it is very likely that they will not believe in their ability to interact with academic content in Second Life (AS). Interestingly, they are also less likely to believe in their ability in the content knowledge. This is a dramatic finding; students perceive ‘functionality in virtual worlds’ and ‘knowledge of content’ as correlated, even if they may not be in reality. (I think this is a unique finding in the literature - Steven?)
Sense of presence - communicating effectively with others and gesturing is a critical dimension of functionality in virtual worlds
The content comes into play as a significant dimension of self-efficacy. It is easy to focus on the virtual world, but really, it's the content that is the focus.
We have found that AE and AS do exist as self-efficacy factors in virtual world learning. We've expanded the meanings to a virtual world (AE includes avatars for instance). We have expanded the AE/AS conceptions of computer self-efficacy into the virtual world environment? We know that they exist? We understand those relationships more?
The results offer some implications for instructional design in virtual worlds. When designing instruction, it is important to consider all three dimensions of self-efficacy. Regarding functionality in virtual worlds, students need to know how to navigate, communicate with others, and interact with objects. This must happen in order for students to successfully interact with the virtual world-mediated content. Along with Wang and Hsu (2009), we recommend gauging students’ prior experience with virtual worlds, in order to help determine background knowledge in this setting. A comprehensive survey can capture a lot of information on a learner’s technical skill in virtual worlds, beliefs, gaming experience and gender. Knowing these elements can help a designer/teacher craft what kind of training the students will need in order to feel able to control their avatar in the space. There are plenty of tutorials in SL already created. While technical support emerged in Wang and Hsu’s (2009) study, they also supported students to use the communication tools and actively participate in Second Life®. The instructor designed a sequence of activities to support students to gain competence in these areas.
Mayrath et al. (2009) suggest that if learners are new to virtual worlds, the activities can be initially simple and gradually grow more technically complex (example?). It’s important to keep this in mind; do not design a very complicated object if it doesn’t need to be very complicated. The simpler, the better, especially at first. They need to believe in their ability to interact with this, as it relates to their belief in the ability of the content as a whole. We suggest designing objects which will provide students with interaction and immediate feedback concerning the content, and one that sends the teacher feedback too.
Another factor to consider is their self-efficacy concerning the academic content in general. Since belief in the content as a whole is a factor, we recommend teaching the content in multiple ways, and SL can be one part. If they “get it” in other environments, they may “get it” in SL more easily. Those doing well with the content may not have to be faced with learning SL and the content as much.
Conclusion
This study is significant since it statistically identifies the multiple dimensions of self-efficacy students perceive in a virtual world learning space. We have confirmed that self-efficacy regarding virtual world learning goes beyond general self-efficacy (of accounting content) or computer self-efficacy. We are confirming the ae/as idea in virtual worlds. Knowing how to use or access SL does not guarantee learning of content (but it helps). Students that felt high self-efficacy in interacting with the objects were more likely to have high self-efficacy in learning content. This gives us concrete areas to pinpoint for instructional design. For instance, targeting ‘functionality in virtual worlds,’ a designer/teacher can specifically think about supporting students concerning navigation, communication with others, and interaction with objects. This is a baseline need before meaningful learning happens in SL. Bad design of SL can negatively impact beliefs in learning the accounting concepts.
This study stands apart from most by considering the actual content being learned in the virtual world (in this case, accounting). Often in virtual world studies, they just look at the virtual world and don’t look deeply at the content itself.
This study builds upon the previous work done on understanding self-efficacy in complex environments such as SL.
Those that believe in their ability to use SL and interact with objects are more likely to believe in their ability to learn accounting concepts. This is very important. If designed correctly, students who have trouble in accounting may be helped with their performance.
There are a few limitations to this study, the biggest one being that the survey was taken by students in a particular accounting class in one university in the Southeast. It is possible that the discipline, or design of the SL activity, or teacher, significantly influenced the results. Next steps, we could work at further validating these factors. It’s a survey so they are all perceptions. But, perceptions are important. Students perceive a connection between ability to do the content, and ability to get around SL, whether real or imagined. Regarding data analysis, the results are rooted in correlations, which help predict relationships of the dimensions, but do not show any cause. While ‘functionality in virtual worlds’ is related to ‘knowledge of content’, we do not know if one causes the other, or how it influences. There could be other variables affecting this relationship. A deeper look past surveys could be helpful.
Only extra credit people did it - they might have skewed the results.
So does using SL help students learn accounting concepts? Next, we will look at performance measures.
References
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Questions for Chuck and Patsy: The survey number is high. How should we graphically show the data?
Steven: Will talk more about the tutorials the students used to prepare them for the assignments. He will expand on the part where I say it's good to have objects that give immediate feedback. This feedback allows students to interact with the equation and retry.
Random Notes to Incorporate:
Functionality = AE
Interacting with objects = AS
We are also looking at content.
SL is unique from other applications in that you have a sense of place and body.
It is also more technically complex than other applications.
Self-efficacy is a concern - getting around it, but also learning the content.
Self-efficacy is dimensional with regards to learning, especially with technology. What are the dimensions, how has this been studied in the past? Johnson went with AS and AE; a general self-efficacy was not enough to fully appreciate learners' abilities/needs. We are going to identify the dimensions of self-efficacy in SL, rather than basic computer software. SL has the extras like avatars, communicating with others, etc. We are going to look at it from the perspective of an academic class as well.
We need to define AE and AS in our context.
How was self-efficacy been studied with regards to virtual worlds? Merchant and Chow both looked at it in different ways. Merchant was more general self-efficacy in the content (chemistry), and Chow looked at usability, ease of use, etc. While these are both promising and drove our research, we want to expand on those findings by looking at the dimensions of self-efficacy that comes with learning in this environment.
Chow: Ease of use was an issue.
Steven gave students questions to measure self-efficacy, and we wanted to see if the questions fell into these categories (AE and AS). Content emerged as important. Those believing in their ability to use the LOs were more likely to believe in their ability to understand the equation; likewise, those understanding the equation were more likely to believe in their ability to use the LOs. We want to understand these factors more in our next research; determine some causation.
Next Steps: In this look, we are simply measuring whether they have self-efficacy or not. We are not looking into how they got self-efficacy in the first place. Next time we will look at the influences of certain approaches/guides to help students gain self-efficacy. For instance, Steven created a tutorial -- when students used this, their questions about how to use SL went down dramatically. If they have more AS, then their AE and content are likely to be positively influenced. What should be in a good orientation?
At the end - we know more about the dimensions of self-efficacy. Measuring self-efficacy in one way is not enough. There is AE, AS, and the content itself.
Abstract
Virtual worlds offer learners an enhanced sense of user presence and community, opportunities for experiential experiences, and user-centered design of the environment. However, virtual worlds are more technically complex than technologies typically used in educational settings and require students to interact in novel ways for learning to occur. Self-efficacy, the beliefs a person has about her capabilities to successfully perform a particular behavior or task, could be a critical element toward understanding student learning with the virtual world. The purpose of our study is to explore the dimensionality of students’ self-efficacy concerning learning academic content in the virtual world of Second Life. Students in an accounting class participated in several virtual world activities to learn content. Through analysis of a survey, three dimensions of self-efficacy were identified: functionality in virtual worlds; content mediated by virtual world; and content. The findings of this study offer an insight into the critical instructional design issues that must be addressed in order for effective learning to be realized in virtual worlds.
Introduction
[Aimee will expand] Technologies that place the user at the center of learning are rapidly being incorporated in higher education. The features of social media complement the constructivist philosophy of teaching and learning, allowing learners to create, co-create and share knowledge with a global audience beyond classroom walls. In addition, social media is tremendously popular in learners’ social lives.
One such innovative technology being integrated in educational environments is the three-dimensional virtual world. Most virtual worlds, such as Second Life, physically resemble three-dimensional Earth in varying degrees, with typical depictions of land, sky, and water. Both designers and users can shape the design, content and objectives of the world, which is perpetual and persistent (Book, 2004). [Expand on this more, give examples maybe]
SL is different. Unlike most other social media applications, virtual worlds stimulate a feeling of actually being located in the virtual space (Mennecke, Hassall, & Triplett, 2008). Users are represented by avatars, simulated bodies in which users sensually perceive the virtual world. Compared to other online technologies, there is a heightened sense of user presence due to the embodied nature of avatars. In contrast to a video game in which an avatar represents a character, in a social virtual world, the avatar is intended to represent the user. Loke (2009) explains, “SL is not simply a game where players, detached from their avatars, control the avatars for pure entertainment…It’s not simply a uniform, but self-representation” (p. 148). With roots in social media and games, virtual worlds are predicated on social interaction. Virtual worlds are multi-user, meaning that multiple users share the same space and interact in ‘real time’. Regarding interaction, avatars occupy the same space and communication is mediated by the body; written text, spoken voice and body language. Because of this shared experience, common ground can be created and sustained, eliciting a feeling of co-presence, that the user is really with another person (Jarmon, 2009). As the user directs the avatar through the 3D space, the computer generates graphics in real time to give the user visual and auditory feedback on their position in the environment (Jones, Morales, & Knezek, 2005). Just as humans in the ‘real world’, avatars dynamically interact with objects and each other.
They are becoming more integrated into educational environments. Past studies have found that the virtual world learning environment engages students (Hornik & Thornburg, 2010; Meggs et al., 2011; Mennecke et al., 2008), and can lead to improved performance (Hornik & Thornburg, 2010). The unique affordances of virtual worlds help to explain these findings. First, they have been found to support a sense of community among learners. Regarding community, McKerlich, Rils, Anderson, and Eastman (2011) found that participants did in fact experience a community of inquiry in a virtual world learning environment. Specifically three types of user presence were identified: social (avatar expression, group activities), cognitive (discussions, building) and teaching (text, IM, notecards). It provided a forum for wide collaboration with the potential to link students to the professional world (Meggs). The affordances of the space also allow novel ways to create content and sense of place (Hornik & Thornburg, 2010), which supports multiple learning styles (Meggs et al., 2011). Due to the open-ended nature and customizability of the environment, it can be used for all kinds of disciplines and objectives.
It has the ability to be free from worldly time and space hindrances as well. Meggs, Greer, and Collins (2011) found that the use of SL facilitated instructional practices that allowed for experiential activities which would not have been otherwise available. By learning in virtual worlds, students can make connections to subjects previously seen as abstract. Merchant talks about them learning chemistry concepts by rotating chemistry models through their avatars. Students can receive instant feedback through interacting with objects and from others in the environment. For example, Meggs et al. (2011) found that virtual note cards aided students in making corrections to their thinking (Steven kind of did this).
But there are hindrances; SL is tough. The learning curve required for SL has been documented by many (Collins, personal communication; Mayrath, Traphagan, Heikes, & Trivedi, 2009; Sanchez, 2007). One consistent theme in the literature is that learners often report technical difficulties when participating in SL (Mayrath et al., 2009; Mennecke et al., 2008; Sanchez, 2007). Student technical skill and experience with virtual worlds significantly impact a student’s learning experience. Students often report difficulties with the interface (Mennecke et al., 2008), with interaction with objects like media or notecards (deNoyelles, 2012), with navigation (deNoyelles, 2012), and with communication with others (Mennecke et al., 2008). Chow et al. (2012) found that ease of use was a factor, and they identified a need to boost self-confidence when using the system.This makes it difficult or impossible to build and shape content within the environment (deNoyelles, 2012). Merchant et al. (2012) found that usability influenced the learning of content. All of these factors impact learning. Supporting students to learn content is difficult here.
(So they need to feel control of their avatars and with the objects they need to interact with in order to get a learning benefit from it.)
(SL is different and tough; Self-efficacy is important) In order to navigate through the environment and customize content (ease the use), the student must take control and make decisions, leading to immersion in the learning process and positively affecting motivation (Dieterle & Clarke, 2007; Malone & Lepper, 1987). However, in order to take control and make decisions in the virtual world, one must perceive an adequate level of self-efficacy, defined as beliefs a person has about her capabilities to successfully perform a particular behavior or task (Merchant, Goetz, Keeney-Kennicutt, Kwok, Cifuentes, & Davis, 2012). Bandura (1997) described self-efficacy as "beliefs in one's capabilities to organize and execute the courses of action required to produce given attainments" (p. 3). It is thought that self-efficacy influences the behavior someone is willing to engage it, the extent to which the behavior is successful, the persistence one maintains in the face of obstacles, and coping mechanisms used when encountering adverse situations (Johnson, 2005). These characteristics make self-efficacy a key characteristics for leveraging the promise of virtual worlds. Self-efficacy is an area that is not fully understood in the virtual world environment, which is concerning given that virtual worlds are technically more complex than other kinds of social media being used in classrooms. Self-efficacy could be a critical element toward understanding student learning within the virtual world. In particular, a factor associated with self-efficacy is the ability to interact and control the learning environment (Bandura, 1993).
(Self-efficacy has dimensions) How have others studied self-efficacy? Similar to the current interest in self-efficacy with respect to virtual worlds, the information systems community examined this construct in the late 1990's while investigating causes related to end-user's adoption and use of computer technology. This research focused on the need to move beyond a general self-efficacy measure to examine self-efficacy as it related specifically to the task in question - computer self-efficacy (Compeau and Higgins, 1995; Marakas, Mun, and Johnson,1998; Johnson, 2005). In this research computer self-efficacy was referred to a users "judgement of one's capability to use a computer" (Compeau and Higgins, 1995, p. 192). Marakas et al. (1998) proposed that like general self-efficacy, 'general' computer self-efficacy was too broad a construct and argued for the use of task specific measures. Johnson (2005) defined these task specific constructs as Application-environment computer self-efficacy (AE) and Application-specific computer self-effiacy (AS). AE is an individual's belief in their ability to complete tasks common to an application environment (e.g. navigate in SL). AS is an individual's belief in their ability to complete a task specific to an application (e.g. interacting with objects within learning objects within SL). It is important when studying the impact of self-efficacy within virtual worlds to take use these more nuanced constructs to be able to examine the various aspects in a learner's belief that can influent their use and eventual benefit that may derive from learning with virtual worlds. That is, a learner must first be able to use the SL platform in general (AE) before they can be expected to be comfortable to work with learning objects designed for a specific learning content area (AS) (in our study, we test this out). As argued by Marakas et al. (1998, p. 129), "by focusing on the appellation independent of the task being performed with it, we can assess an individual's perception of ability to use the tool without constraining or bounding that assessment with a task situation requiring cross-domain knowledge".
(We need to look at the dimensions of self-efficacy in SL) Research about self-efficacy and virtual worlds has begun. Merchant et al. (2012) examined general self-efficacy (self-efficacy for learning chemistry) in SL and found a relationship between self-efficacy and student performance. Being able to control/interact with the environment may influence self-efficacy about learning the content (Merchant). They also found a relationship between the usability of SL and self-efficacy (content), as well as an indirect relationship between the features of SL and self-efficacy (content). They found that self-efficacy has a significant impact on learning content. However, the question of whether usability affects self-efficacy or if self-efficacy affects usability in understanding its impact on learners with regard to virtual worlds can be underscored by Chow et al. (2012) who examined the relationship between computer self-efficacy and learners perceived ease-of use and usefulness of SL (opposite to that of Merchant et al, (2012). A potential limitation with these two studies is that each only examined the concept of general self-efficacy. It is our contention that while the relationship between perceived usability and features is important, it is as important for students to feel they have the ability to use such environments in general and to use immersive learning models more specifically (completing tasks within?).
The purpose of our study is to better understand the dimensionality of the space according to students relating to the academic content in virtual worlds, and to examine the relationships of the various dimensions of virtual world self-efficacy. (Steven asked questions related to general self-efficacy, SL self-efficacy, and 3 dimensions came out).
This paper will therefore examine the relationships between AE-SL (get around SL like navigation) and AS-SL (interacting with objects in SL) and also a third self-efficacy, "content-matter" self-efficacy. It is our belief that perceptions of one's belief in having learned a skill within a visual world environment, they must first believe in their ability to use the environment in general, followed by the belief in their ability to utilize tools within the virtual world. The findings of this study offer an insight into the critical instructional design issues that must be addressed before effective learning can occur in virtual worlds.
Methodology
This research took place in a Financial Accounting course taught in the Spring 2011 semester at a very large university in the southeast United States. The course had a total enrollment of 772 students. The course is a required class and is taught as a video-streaming course which means that students have the option to attend class or watch the classroom presentation via streaming video. The virtual world of Second Life was utilized as a supplement to the class and geared heavily towards the foundational material in the beginning of the course. A foundational learning concept in financial accounting is the accounting equation which states as: Assets = Liabilities + Stockholder's Equity. At first blush it looks like a simple algebraic equation, which it is. But within the realm of financial accounting, adjustments to the variables in the equation (Assets, Liabilities and Stockholder's Equity) are described using the terms 'debit' and 'credit'. In short, any increase to an Asset account requires a debit and any increase in a Liability or Equity account requires a credit. while the reverse is true when decreasing the accounts. It gets more complicated when considering the accounts that compose the equity variable. Without understanding these basic concepts, students are destined for early withdrawal, failure or a semester of considerable time and effort to earn a passing grade.
To help students understand the accounting equation (Assets = Liabilities + Stockholders Equity), a model of it was built in Second Life. This model allowed students to visualize how a debit or credit would increase or decrease the account type and impact the accounting equation, going beyond an abstract algebraic expression to something tangible that can be seen, touched and interacted with (Include Figure here). Two types of these learning models were developed. One type allowed the students to interact with the various parts of the model (Assets, Liabilities, Equity). The students had to "talk" (via text chat) to the models and provide the key words "debit" and/or "credit" followed by a value, after which they would visually see the effect of the command on the 3-D asset increasing or decreasing within the virtual world. They would also receive text-based feedback from the model, such as "Assets 'debited' standby for an Increase". Students used this model to complete various assignments. The first assignment simply had students learn the chat commands to interact with the model, while the next two assignments had students interact with the model with sets of various accounting transactions pertinent to the section of the course that they were learning. The second type of 3-D accounting equation model was in the form of a tutorial. These models were designed to help a student learn basic accounting equations. They could interact with these tutorial models and, for example, learn how to record a collection of cash on account. Additionally, a construct commonly used in teaching financial accounting, the t-account, was also modeled. A t-account is a representation of an account and is used to distinguish the effects of a debit or credit on a specific account balance. Within Second Life, students (through avatars) were able to walk onto a T-account and turn into a debit or credit (interacting with the equation through their simulated bodies). They were then given various accounts and had to determine what was needed to either increase or decrease the account balance (debit or credit) and walk to the proper side (debit or credit) of the t-account. Students would receive feedback from the model as they made their choices.
The majority of these assignments took place during the initial part of the course (all of the 3-D accounting equation assignments) while the t-account assignment was completed during the latter part of the course. Student assignments were captured and sent to a database for grading, and all assignment work was completed within the SL environment.
Data Sources and Collection
After finishing the various Second Life assignments, students were asked to complete surveys related to their experiences. While the survey instrument collected various measures, this paper focuses only on the self-efficacy measures. The measures were constructed based on the methodology described in Marakas, Yi and Johnson (1998). The research data is the result of surveys (n=1377) that were presented to the students at the beginning of the semester and included questions related to self-efficacy. Specifically, the questions related to students perceptions pertaining to their ability to use the Second Life environment (navigation, communication, etc.), their ability to use the 3-D learning objects within Second Life, and their ability to understand the basic accounting concepts. Students received extra credit for completing the surveys.
Data Analysis (Aimee will talk to Chuck more about this)
To assess the dimensionality of student ratings of self-efficacy, the authors used Guttman's image factor analysis (Guttman, 1953). The variables are considered in two parts: that which can be predicted from the rest of the variables in the set (the image) and that which is not predictable from those variables (the anti-image). While the images are similar to common factors, the anti-images are similar to unique factors (Desjardins, 2010). Unlike common factor analysis, this is a multiple correlation approach (Desjardins, 2010). For all of the data, a pattern matrix and correlation matrix were generated.
Results
Three dimensions of self-efficacy were extracted from the data using a pattern matrix. These are: (1) functionality in virtual worlds (application-environment computer self-efficacy); (2) content mediated by SL (application-specific computer self-efficacy); and (3) content. Each category will be explored below, with reference to the statistically strongest survey items for each.
Dimension 1: Functionality in Virtual World (should we rename this AE?)
In line with previous literature, being able to technically function in the virtual world (usability?) emerged as a unique dimension of self-efficacy. Table 1 lists the statements and their corresponding strength.
Based on these results, feeling able to control the avatar as it/he/she moves, walks, and flies through the space is critical. Communication with others, such as chatting in text and avatar gestures, is also a factor. Feeling able to interact with objects in the world also emerges. These are all crucial skills that are necessary for student learning in SL to take place. On an interesting note, these results can be expanded to the ‘real world’ as well. To learn effectively, students must feel able to control their bodies in space, communicate with others, and interact with the world. These are the basic elements; simply to function in the virtual world (learning is not addressed here yet).
*In the intro, positives include community and user presence (communication), transcend the real, and interaction with content (interact with objects, world).
Dimension 2: Content Mediated by Virtual World (should we rename this AS?)
Another dimension of self-efficacy is the students’ belief in their ability to interact with the academic content (in this case, accounting learning objects) mediated by the virtual world. Table 2 displays the survey items in this dimension.
Feeling able to “manipulate” and “use” learning objects embedded in the virtual world emerges as its own dimension of self-efficacy. Being able to use objects (like credits and debits) in order to “interact” with the equation also comes out. This is an interesting notion; in this case, users also interact with the accounting equation by standing in a certain spot, which is a novel way to learn accounting.
Certainly, this dimension is related to the first dimension, ‘functionality in virtual worlds.’ One must move their avatar through the virtual world space in order to get to the accounting objects. Another factor to consider is their self-efficacy concerning the academic content in general.
Dimension 3: Academic Content
Finally, self-efficacy regarding the accounting content emerged as the final dimension (Table 3). Students’ beliefs in the ability to properly identify the debit and credit part of a transaction were important. Note that these statements are completely separate from the activities experienced in SL.
A correlation matrix of the data reveals that these three dimensions of self-efficacy are highly correlated (Table 4). For instance, if students believe in their ability to navigate in the SL classroom, they are also likely to believe in their ability to manipulate accounting content in SL (.730), and more likely to believe in their knowledge of the accounting content (.677). Following this line of thinking, if one does not believe in their ability to use the accounting equation in SL, they are less likely to function well in SL, and less likely to have high self-efficacy regarding their knowledge of the accounting content. The implications of this are discussed in the next section.
Discussion
The implications of this study are powerful, as it supports our assertion that a single construct of self-efficacy regarding virtual worlds is not sufficient to gauge whether students will be successful learners in these environments. Our results identify three dimensions of self-efficacy that are relevant for learners and meaningful learning. It is clear that students must feel able to technically navigate and interact with the virtual world (other studies support this like Chow and Merchant) (AE). If they cannot, it is very likely that they will not believe in their ability to interact with academic content in Second Life (AS). Interestingly, they are also less likely to believe in their ability in the content knowledge. This is a dramatic finding; students perceive ‘functionality in virtual worlds’ and ‘knowledge of content’ as correlated, even if they may not be in reality. (I think this is a unique finding in the literature - Steven?)
Sense of presence - communicating effectively with others and gesturing is a critical dimension of functionality in virtual worlds
The content comes into play as a significant dimension of self-efficacy. It is easy to focus on the virtual world, but really, it's the content that is the focus.
We have found that AE and AS do exist as self-efficacy factors in virtual world learning. We've expanded the meanings to a virtual world (AE includes avatars for instance). We have expanded the AE/AS conceptions of computer self-efficacy into the virtual world environment? We know that they exist? We understand those relationships more?
The results offer some implications for instructional design in virtual worlds. When designing instruction, it is important to consider all three dimensions of self-efficacy. Regarding functionality in virtual worlds, students need to know how to navigate, communicate with others, and interact with objects. This must happen in order for students to successfully interact with the virtual world-mediated content. Along with Wang and Hsu (2009), we recommend gauging students’ prior experience with virtual worlds, in order to help determine background knowledge in this setting. A comprehensive survey can capture a lot of information on a learner’s technical skill in virtual worlds, beliefs, gaming experience and gender. Knowing these elements can help a designer/teacher craft what kind of training the students will need in order to feel able to control their avatar in the space. There are plenty of tutorials in SL already created. While technical support emerged in Wang and Hsu’s (2009) study, they also supported students to use the communication tools and actively participate in Second Life®. The instructor designed a sequence of activities to support students to gain competence in these areas.
Mayrath et al. (2009) suggest that if learners are new to virtual worlds, the activities can be initially simple and gradually grow more technically complex (example?). It’s important to keep this in mind; do not design a very complicated object if it doesn’t need to be very complicated. The simpler, the better, especially at first. They need to believe in their ability to interact with this, as it relates to their belief in the ability of the content as a whole. We suggest designing objects which will provide students with interaction and immediate feedback concerning the content, and one that sends the teacher feedback too.
Another factor to consider is their self-efficacy concerning the academic content in general. Since belief in the content as a whole is a factor, we recommend teaching the content in multiple ways, and SL can be one part. If they “get it” in other environments, they may “get it” in SL more easily. Those doing well with the content may not have to be faced with learning SL and the content as much.
Conclusion
This study is significant since it statistically identifies the multiple dimensions of self-efficacy students perceive in a virtual world learning space. We have confirmed that self-efficacy regarding virtual world learning goes beyond general self-efficacy (of accounting content) or computer self-efficacy. We are confirming the ae/as idea in virtual worlds. Knowing how to use or access SL does not guarantee learning of content (but it helps). Students that felt high self-efficacy in interacting with the objects were more likely to have high self-efficacy in learning content. This gives us concrete areas to pinpoint for instructional design. For instance, targeting ‘functionality in virtual worlds,’ a designer/teacher can specifically think about supporting students concerning navigation, communication with others, and interaction with objects. This is a baseline need before meaningful learning happens in SL. Bad design of SL can negatively impact beliefs in learning the accounting concepts.
This study stands apart from most by considering the actual content being learned in the virtual world (in this case, accounting). Often in virtual world studies, they just look at the virtual world and don’t look deeply at the content itself.
This study builds upon the previous work done on understanding self-efficacy in complex environments such as SL.
Those that believe in their ability to use SL and interact with objects are more likely to believe in their ability to learn accounting concepts. This is very important. If designed correctly, students who have trouble in accounting may be helped with their performance.
There are a few limitations to this study, the biggest one being that the survey was taken by students in a particular accounting class in one university in the Southeast. It is possible that the discipline, or design of the SL activity, or teacher, significantly influenced the results. Next steps, we could work at further validating these factors. It’s a survey so they are all perceptions. But, perceptions are important. Students perceive a connection between ability to do the content, and ability to get around SL, whether real or imagined. Regarding data analysis, the results are rooted in correlations, which help predict relationships of the dimensions, but do not show any cause. While ‘functionality in virtual worlds’ is related to ‘knowledge of content’, we do not know if one causes the other, or how it influences. There could be other variables affecting this relationship. A deeper look past surveys could be helpful.
Only extra credit people did it - they might have skewed the results.
So does using SL help students learn accounting concepts? Next, we will look at performance measures.
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